Optimized CRISPR-Cas9 Genome Editing for <i>Leishmania</i> and Its Use To Target a Multigene Family, Induce Chromosomal Translocation, and Study DNA Break Repair Mechanisms
Bibliographic record
Abstract
Leishmania parasites cause human leishmaniasis. To accelerate characterization of Leishmania genes for new drug and vaccine development, we optimized and simplified the CRISPR-Cas9 genome-editing tool for Leishmania . We show that co-CRISPR targeting of the miltefosine transporter gene and serial transfections of an oligonucleotide donor significantly eased isolation of edited mutants. This cotargeting strategy was efficiently used to delete all 11 members of the A2 virulence gene family. This technical advancement is valuable, since there are many gene clusters and supernumerary chromosomes in the various Leishmania species and isolates. We simplified this CRISPR system by developing a gRNA and Cas9 coexpression vector which could be used to delete genes in various Leishmania species. This CRISPR system could also be used to generate specific chromosomal translocations, which will help in the study of Leishmania gene expression and transcription control. This study also provides new information about double-strand DNA break repair mechanisms in Leishmania .
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".